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<h1>Codebook for Garcia and Wimpy PSRM Reproduction</h1>

<h2>Variables (in order of dataset):</h2>

<h3>ccode:</h3>

<ul>
<li>Label: COW Code</li>
<li>Description: Country code from the Correlates of War Project (Ghosn et al. 2004)</li>
<li>Notes: Primarily used for merging and indexing</li>
</ul>

<hr>

<h3>country</h3>

<ul>
<li>Label: Country Name</li>
<li>Description: Country of observation</li>
</ul>

<hr>

<h3>year</h3>

<ul>
<li>Label: Year</li>
<li>Description: observational year</li>
</ul>

<hr>

<h3>agv:</h3>

<ul>
<li>Label: Sum of Anti-Government Violence Events</li>
<li>Description: Sum of Anti-Government Violence Events per country-year</li>
<li>Source: Social Conflict in Africa Database (Salehyan et al. 2012)</li>
<li>Coding: count of events</li>
</ul>

<hr>

<h3>agvy1_spatlag:</h3>

<ul>
<li>Label: Main Spatial Lag</li>
<li>Description: spatially lagged anti-government violence</li>
<li>Source: SCAD</li>
<li>Coding: first created from agv vector and then multiplied by our contiguity weights matrix</li>
</ul>

<hr>

<h3>mobile</h3>

<ul>
<li>Label: Mobile</li>
<li>Description: Level of mobile phone penetration</li>
<li>Source: International Telecommunications Union</li>
<li>Coding: Number of subscribers per 1,000 people</li>
</ul>

<hr>

<h3>internet:</h3>

<ul>
<li>Label: Internet</li>
<li>Description: Level of internet penetration</li>
<li>Source: International Telecommunications Union</li>
<li>Coding: Percent of population using internet</li>
</ul>

<hr>

<h3>agvy1_ylag:</h3>

<ul>
<li>Label: Main Lagged DV</li>
<li>Description: one-year temporally lagged anti-government violence</li>
<li>Source: SCAD (Salehyan et al. 2012)</li>
<li>Coding: previous years value for agv for each country year</li>
</ul>

<hr>

<h3>repress_ylag:</h3>

<ul>
<li>Label: Lagged Repression</li>
<li>Description: whether or not the government repressed anti-government violence in previous year</li>
<li>Source: SCAD (Salehyan et al. 2012)</li>
<li>Coding: 1=repression, 0=no repression</li>
</ul>

<hr>

<h3>percent_pop_refugee:</h3>

<ul>
<li>Label: Percent of Population Refugee</li>
<li>Description: percentage of the population made up of refugees</li>
<li>Source: UN High Commission for Refugees (UNHCR) Population Database</li>
<li>Coding: percentage of the population made up of refugees</li>
</ul>

<hr>

<h3>polity:</h3>

<ul>
<li>Label: Polity IV</li>
<li>Description: Polity autocracy-democracy Score</li>
<li>Source: Polity IV (Marshall et al. (2012))</li>
<li>Coding: &#8211;10&#8211;10 (where &#8211;10 is most autocratic and 10 is most democratic, our data run from &#8211;9&#8211;9)</li>
<li>Notes: We also used a squared version of this variable (Polity2)</li>
</ul>

<hr>

<h3>polity2:</h3>

<ul>
<li>Label: Polity Squared</li>
<li>Description: Polity autocracy-democracy Score</li>
<li>Source: Polity IV (Marshall et al. (2012))</li>
<li>Coding: 0 to 81</li>
<li>Notes: We also used the original version of this variable (Polity)</li>
</ul>

<hr>

<h3>ln_gdppc:</h3>

<ul>
<li>Label: ln(GDP Per Capita)</li>
<li>Description: Gross domestic product per capita</li>
<li>Source: World Bank</li>
<li>Coding: Natural log of gross domestic product per capita</li>
</ul>

<hr>

<h3>ln_pop:</h3>

<ul>
<li>Label: ln(population)</li>
<li>Description: Total population for each country-year</li>
<li>Source: World Bank</li>
<li>Coding: natural log of total population</li>
</ul>

<hr>

<h3>ethnic:</h3>

<ul>
<li>Label: Ethnic Fractionalization</li>
<li>Description: Degree of ethnic fractionalization</li>
<li>Source: Alesina et al. (2003)</li>
<li>Coding: Herfindahl index of heterogeneity</li>
</ul>

<hr>

<h3>election:</h3>

<ul>
<li>Label: Election in Year</li>
<li>Description: whether or not an election occurred in a given country-year</li>
<li>Source: IDEA Voting Database</li>
<li>Coding: 1=election in year, 0=no election in year</li>
</ul>

<hr>

<h3>urban:</h3>

<ul>
<li>Label: Urbanization</li>
<li>Description: Level of urbanization for each country-year</li>
<li>Source: World Bank</li>
<li>Coding: percentage of population living in an urban area</li>
</ul>

<hr>

<h3>center_agvy1_spatlag:</h3>

<ul>
<li>Label: Centered Spatial Lag</li>
<li>Description: Used in our substantive effects section</li>
<li>Source: generated in Stata from our spatial lag</li>
<li>Coding: spatial lag centered to have mean of zero</li>
</ul>

<hr>

<h3>center_mobile:</h3>

<ul>
<li>Label: Centered Mobile Variable</li>
<li>Description: Used in our substantive effects section</li>
<li>Source: generated in Stata from mobile variable</li>
<li>Coding: mobile centered to have mean of zero</li>
</ul>

<hr>

<h3>center_mobile1:</h3>

<ul>
<li>Label: Mobile moving from 0&#8211;5</li>
<li>Description: Used in our substantive effects section</li>
<li>Source: generated in Stata from mobile variable</li>
<li>Coding: mobile rescaled for 0&#8211;5 change</li>
</ul>

<hr>

<h3>center_mobile2:</h3>

<ul>
<li>Label: Mobile moving from 5&#8211;10</li>
<li>Description: Used in our substantive effects section</li>
<li>Source: generated in Stata from mobile variable</li>
<li>Coding: mobile rescaled for 5&#8211;10 change</li>
</ul>

<hr>

<h3>center_internet:</h3>

<ul>
<li>Label: Centered Internet Variable</li>
<li>Description: Used in our substantive effects section</li>
<li>Source: generated in Stata from our internet variable</li>
<li>Coding: internet centered to have mean of zero</li>
</ul>

<hr>

<h3>center_internet1:</h3>

<ul>
<li>Label: Internet moving from .9&#8211;2</li>
<li>Description: Used in our substantive effects section</li>
<li>Source: generated in Stata from mobile variable</li>
<li>Coding: mobile rescaled for .9&#8211;2 change</li>
</ul>

<hr>

<h3>center_internet2:</h3>

<ul>
<li>Label: Internet moving from 2&#8211;5</li>
<li>Description: Used in our substantive effects section</li>
<li>Source: generated in Stata from mobile variable</li>
<li>Coding: mobile rescaled for 2&#8211;5 change</li>
</ul>

<hr>

<h3>Pipe:</h3>

<ul>
<li>Label: Makes Symbols for Rug Plots</li>
<li>Description: Just a vector of &#8220;|&#8221; which serves as mlabel for rug plots</li>
<li>Source: generated in Stata</li>
<li>Coding: &#8220;|&#8221;</li>
</ul>

<hr>

<h3>tag_mobile:</h3>

<ul>
<li>Label: Used to Remove Duplicate Values in Rug Plot</li>
<li>Description: This variable simply keeps the &#8220;|&#8221; from stacking in the plot</li>
<li>Source: generated in Stata</li>
<li>Coding: 1&#8211;0 with each unique value of mobile=1</li>
</ul>

<hr>

<h3>mobile_graph:</h3>

<ul>
<li>Label: in-sample mobile</li>
<li>Description: Variable generated for graphs</li>
<li>Source: generated in Stata</li>
<li>Coding: in-sample range of per capita mobile subscribers</li>
</ul>

<hr>

<h3>tag_internet:</h3>

<ul>
<li>Label: Used to Remove Duplicate Values in Rug Plot</li>
<li>Description: This variable simply keeps the &#8220;|&#8221; from stacking in the plot</li>
<li>Source: generated in Stata</li>
<li>Coding: 1&#8211;0 with each unique value of internet=1</li>
</ul>

<hr>

<h3>internet_graph:</h3>

<ul>
<li>Label: in-sample internet</li>
<li>Description: Variable generated for graphs</li>
<li>Source: generated in Stata</li>
<li>Coding: in-sample range of percentage internet users</li>
</ul>

<hr>

<h3>where:</h3>

<ul>
<li>Label: Location Variable for Graphs 1&#8211;5</li>
<li>Description: Determines where the &#8220;|&#8221; goes in the graph</li>
<li>Source: generated in Stata</li>
<li>Coding: positional for graph (&#8211;5)</li>
</ul>

<hr>

<h3>where2:</h3>

<ul>
<li>Label: Location Variable for Graph 5</li>
<li>Description: Determines where the &#8220;|&#8221; goes in the graph</li>
<li>Source: generated in Stata</li>
<li>Coding: positional for graph (&#8211;5.7)</li>
</ul>

<hr>

<h3>demonstrations:</h3>

<ul>
<li>Label: Total Number of Demonstrations</li>
<li>Description: number of demonstrations from SCAD</li>
<li>Source: SCAD (Salehyan et al. 2012)</li>
<li>Coding: total number of demonstrations per country year</li>
</ul>

<hr>

<h3>demoy1_spatlag1:</h3>

<ul>
<li>Label: Demonstrations slag</li>
<li>Description: spatially lagged demonstrations</li>
<li>Source: SCAD (Salehyan et al. 2012)</li>
<li>Coding: demonstrations vector multiplied by weights matrix</li>
</ul>

<h3>demo_ylag:</h3>

<ul>
<li>Label: Lagged Demonstrations</li>
<li>Description: one-year temporally lagged demonstrations</li>
<li>Source: SCAD (Salehyan et al. 2012)</li>
<li>Coding: previous years value for demonstrations for each country year</li>
</ul>

<hr>

<h3>riots:</h3>

<ul>
<li>Label: Total Number of Riots</li>
<li>Description: number of riots from SCAD</li>
<li>Source: SCAD (Salehyan et al. 2012)</li>
<li>Coding: total number of riots per country year</li>
</ul>

<hr>

<h3>rioty1_spatlag1:</h3>

<ul>
<li>Label: Riots slag</li>
<li>Description: spatially lagged riots</li>
<li>Source: SCAD (Salehyan et al. 2012)</li>
<li>Coding: riots vector multiplied by weights matrix</li>
</ul>

<hr>

<h3>riots_ylag:</h3>

<ul>
<li>Label: Lagged Riots</li>
<li>Description: one-year temporally lagged riots</li>
<li>Source: SCAD (Salehyan et al. 2012)</li>
<li>Coding: previous years value for riots for each country year</li>
</ul>

<hr>

<h3>strikes:</h3>

<ul>
<li>Label: Total Number of Strikes</li>
<li>Description: number of strikes from SCAD</li>
<li>Source: SCAD (Salehyan et al. 2012)</li>
<li>Coding: total number of strikes per country year</li>
</ul>

<hr>

<h3>strikesy1_spatlag1:</h3>

<ul>
<li>Label: Strikes slag</li>
<li>Description: spatially lagged strikes</li>
<li>Source: SCAD (Salehyan et al. 2012)</li>
<li>Coding: strikes vector multiplied by weights matrix</li>
</ul>

<hr>

<h3>strikes_ylag:</h3>

<ul>
<li>Label: Lagged Strikes</li>
<li>Description: one-year temporally lagged strikes</li>
<li>Source: SCAD (Salehyan et al. 2012)</li>
<li>Coding: previous years value for strikes for each country year</li>
</ul>

<hr>

<h3>terror_total:</h3>

<ul>
<li>Label: Sum of Terror Strikes</li>
<li>Description: number of terror incidents</li>
<li>Source: Global Terrorism Database</li>
<li>Coding: count of terror events per country-year</li>
</ul>

<hr>

<h3>terror_totaly1_spatlag1:</h3>

<ul>
<li>Label: Total Terror Attacks slag</li>
<li>Description: spatially lagged terror_total</li>
<li>Source: Global Terrorism Database</li>
<li>Coding: terror_total vector multiplied by weights matrix</li>
</ul>

<hr>

<h3>terror_totaly1_ylag:</h3>

<ul>
<li>Label: Lagged terror_total</li>
<li>Description: one-year temporally lagged terror_total</li>
<li>Source: Global Terrorism Database</li>
<li>Coding: previous years value for terror_total for each country year</li>
</ul>

<hr>

<h3>terror_gov_target:</h3>

<ul>
<li>Label: Total Terror Strikes Gov Target</li>
<li>Description: number of terror incidents targeting government</li>
<li>Source: Global Terrorism Database</li>
<li>Coding: count of terror events targeting government per country-year</li>
</ul>

<hr>

<h3>terror_gov_targety1_spatlag1:</h3>

<ul>
<li>Label: Terror Gov Target slag</li>
<li>Description: spatially lagged terror_gov_target</li>
<li>Source: Global Terrorism Database</li>
<li>Coding: terror_gov_target vector multiplied by weights matrix</li>
</ul>

<hr>

<h3>terror_gov_targety1_ylag:</h3>

<ul>
<li>Label: Lagged terror_gov_target</li>
<li>Description: one-year temporally lagged terror_gov_target</li>
<li>Source: Global Terrorism Database</li>
<li>Coding: previous years value for terror_gov_target for each country year</li>
</ul>

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